Suchergebnisse - "Multi-robot Reinforcement Learning"

MAMBPO: Sample-efficient multi-robot reinforcement learning using learned world models von Willemsen, Daniel, Coppola, Mario, de Croon, Guido C.H.E.

“… Multi-robot systems can benefit from reinforcement learning (RL) algorithms that learn behaviours in a small number of trials, a property known as sample …”
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Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation von Marchesini, Enrico, Farinelli, Alessandro

“… We study the problem of multi-robot mapless navigation in the popular Centralized Training and Decentralized Execution (CTDE) paradigm. This problem is …”
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From Agents to Robots: A Training and Evaluation Platform for Multi-robot Reinforcement Learning von Liang, Zhiuxan, Cao, Jiannong, Jiang, Shan, Saxena, Divya, Cao, Rui, Xu, Huafeng

“… Multi-robot reinforcement learning (MRRL) is a promising approach to solving cooperation problems and has been widely adopted in many applications …”
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PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas von Nikkhoo, Shahab, Li, Zexin, Samanta, Aritra, Li, Yufei, Liu, Cong

“… Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, particularly in social dilemmas …”
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MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithms von Torbati, Reza J., Lohiya, Shubham, Singh, Shivika, Nigam, Meher S., Ravichandar, Harish

“… Multi-Agent Reinforcement Learning (MARL) has enjoyed significant recent progress thanks, in part, to the integration of deep learning techniques for modeling …”
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Investigating Symbiosis in Robotic Ecosystems: A Case Study for Multi-Robot Reinforcement Learning Reward Shaping von Niu, Xuezhi, Broo, Didem Gurdur

“… This paper presents a bio-inspired reward shaping approach for multi-agent reinforcement learning (MARL) in heterogeneous multi-robot systems, leveraging a …”
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Heterogeneous Multi-Robot Reinforcement Learning von Bettini, Matteo, Shankar, Ajay, Prorok, Amanda

“… Cooperative multi-robot tasks can benefit from heterogeneity in the robots' physical and behavioral traits. In spite of this, traditional Multi-Agent …”
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Effect of Virtual Work Braking on Distributed Multi-robot Reinforcement Learning von Kawano, Hiroshi

“… Multi-agent reinforcement learning (MARL) is one of the most promising methods for solving the problem of multi-robot control. One approach for MARL is …”
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Cooperative multi-robot reinforcement learning: A framework in hybrid state space von Xueqing Sun, Tao Mao, Kralik, J.D., Ray, L.E.

“… This paper presents an approach to cooperative multi-robot reinforcement learning based on a hybrid state space representation of the environment to achieve both task learning and heterogeneous role …”
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Improving Fast Adaptation for Newcomers in Multi-Robot Reinforcement Learning System von Li, Yiying, Zhou, Wei, Wang, Huaimin, Ding, Bo, Xu, Kele

“… Multi-robot system has been adopted as a kind of ubiquitous intelligent systems to perform critical tasks in various fields. In multi-robot systems, …”
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MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithms von Torbati, Reza, Lohiya, Shubham, Singh, Shivika, Nigam, Meher Shashwat, Ravichandar, Harish

“… Multi-Agent Reinforcement Learning (MARL) has enjoyed significant recent progress thanks, in part, to the integration of deep learning techniques for modeling …”
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PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas von Nikkhoo, Shahab, Li, Zexin, Samanta, Aritra, Li, Yufei, Liu, Cong

“… Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, particularly in social dilemmas …”
Volltext

Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation von Marchesini, Enrico, Farinelli, Alessandro

“… We study the problem of multi-robot mapless navigation in the popular Centralized Training and Decentralized Execution (CTDE) paradigm. This problem is …”
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From Multi-agent to Multi-robot: A Scalable Training and Evaluation Platform for Multi-robot Reinforcement Learning von Liang, Zhiuxan, Cao, Jiannong, Jiang, Shan, Saxena, Divya, Chen, Jinlin, Xu, Huafeng

“… This paper introduces a scalable emulation platform for multi-robot reinforcement learning (MRRL …”
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MAMBPO: Sample-efficient multi-robot reinforcement learning using learned world models von Willemsen, Daniël, Coppola, Mario, Guido C H E de Croon

“… Multi-robot systems can benefit from reinforcement learning (RL) algorithms that learn behaviours in a small number of trials, a property known as sample …”
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Hierarchical Deep Reinforcement Learning for Multi-robot Cooperation in Partially Observable Environment von Liang, Zhixuan, Cao, Jiannong, Lin, Wanyu, Chen, Jinlin, Xu, Huafeng

“… Many real-world applications require multi-robot coordination in partially-observable domains such as package delivery, search, and rescue. One typical way to …”
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Simulation of multi-robot reinforcement learning for box-pushing problem von Kovac, K., Zivkovic, I., Basic, B.D.

“… The box-pushing problem represents a challenging domain for the study of object manipulation in a multi-robot environment. Our box-pushing problem is based on …”
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Cooperative Q-learning based on learning automata von Mao Yang, Yantao Tian, Xinyue Qi

“… The theory of learning automata has already been applied in reinforcement learning which is characterized by single-agent and single-stage. This paper proposed …”
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Reinforcement learning method for target hunting control of multi‐robot systems with obstacles von Fan, Zhilin, Yang, Hongyong, Liu, Fei, Liu, Li, Han, Yilin

“… ‐robot reinforcement learning algorithm guided by the potential energy models is presented to perform the hunting, where reinforcement learning principles are combined with the model control …”
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DiNNO: Distributed Neural Network Optimization for Multi-Robot Collaborative Learning von Yu, Javier, Vincent, Joseph A., Schwager, Mac

“… We present DiNNO, a distributed algorithm that enables a group of robots to collaboratively optimize a deep neural network model while communicating over a …”
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